Data science and business informatics
Course Description
Level: Second Level Degree
Degree Class: LM-18 - Computer science
Department: COMPUTER SCIENCE
Admission: Free
CFUs: 120
Duration: 2 years
Website: https://didattica.di.unipi.it/en/master-programme-in-data-science-and-business-informatics/
English
Pisa
- Computer and Data Science (machine learning, data mining, big data analytics, database, algorithms)
- Understanding of business processes (economics, management, marketing, business intelligence and process modelling)
- Fundamentals (statistics, applied mathematics).
The interclass Master’s Degree Course in Data Science and Business Informatics does not have regulated admission. A general curricular requirement for admission is the possession of a three-year degree from the degree classes in Computer Science and Technology (L-31), Information Engineering (L-8), Statistics (L-41), Economics and Business Management (L-18), Economics (L-33), Physical Science and Technology (L-30), Mathematics (L-35) and the corresponding classes under Ministerial Decree 509/1999.
Students with a Bachelor’s Degree from another class having acquired at least 40 CFUs in total in the following fields INF/01, ING-INF/05, MAT/, FIS/, SECS-P/, SECS-S/, ING-IND/35 are also admitted. Proficient knowledge of English at least at level B2 is also required.
In the case of valid degrees obtained abroad, in particular in EU countries, an exception to this general requirement will only be possible with a resolution of the Degree Course Board, based on the candidate’s specific educational background.
The adequacy of personal preparation, particularly in the fundamentals of information science and technology and the English language, is assessed through the evaluation of the educational curriculum, and through an interview conducted by the President of the Course of Study or their delegate.
A general curricular requirement for admission is the possession of a three-year degree from the degree classes in Computer Science and Technology (L-31), Information Engineering (L-8), Statistics (L-41), Economics and Business Management (L-18), Economics (L-33), Physical Science and Technology (L-30), Mathematics (L-35) and the corresponding classes under Ministerial Decree 509/1999.
Students with a Bachelor’s Degree from another class having acquired at least 40 CFUs in total in one or more of the following fields INF/01, ING-INF/05, MAT/, FIS/, SECS-P/, SECS-S/, ING-IND/35 are also admitted. Proficient knowledge of English at least at level B2 is also required.
The adequacy of personal preparation, particularly in the fundamentals of information science and technology and the English language, is assessed through the evaluation of the educational curriculum, and through an interview conducted by the President of the Course of Study or their delegate.
Course Evaluations
Contacts
Presidente del Corso di Laurea
Antonio Frangioni
Email: antonio.frangioni@unipi.it
Referente didattico
Rosaria Mongini
Tel. (+39) 050 2212727
Email: rosaria.mongini@unipi.it
Unità Didattica del Dipartimento di Informatica: https://didattica.di.unipi.it/contatti/
Orario di ricevimento: Ufficio: su appuntamento previo contatto e-mail / telefono (+39) 050 2212727/3110/3162. Sportello: dal martedì al giovedì dalle ore 10.00 alle ore 13.30. Per informazioni scrivere a : datascience@di.unipi.it
Study Plan
For students enrolled in the academic year 2025/2026
Required
- Methods for the specification and verification of business processes (6 CFU) - Primo ciclo semestrale
- Data mining (12 CFU) - Primo ciclo semestrale
- Statistics for data science (9 CFU) - Secondo ciclo semestrale
- Optimization for data science (6 CFU) - Primo ciclo semestrale
Gr2 aziendale e giuridico (9 CFU)
- Financial analysis and performance measurement (9 CFU) - Primo ciclo semestrale
- Business management (9 CFU) - Secondo ciclo semestrale
- Computer science law (6 CFU) - Secondo ciclo semestrale
- Project design & management for data science (6 CFU) - Primo ciclo semestrale
- Analysis and cost management (9 CFU) - Primo ciclo semestrale
- Planning and management control (9 CFU) - Primo ciclo semestrale
- Business organization (9 CFU) - Secondo ciclo semestrale
- Fundamentals of business management (9 CFU) - Primo ciclo semestrale
- Management practice (6 CFU) - Secondo ciclo semestrale
- Strategic and competitive intelligence (6 CFU) - Secondo ciclo semestrale
Gr3 - approfondimento specifico (12 CFU)
- Introduction to logistics (6 CFU)
- Software engineering (6 CFU)
- Legal issues in data science (6 CFU) - Secondo ciclo semestrale
- Decisions, complexity and conflicts (6 CFU)
- Model-driven decision-making methods (6 CFU) - Secondo ciclo semestrale
- Programming for data science (12 CFU) - Primo ciclo semestrale
Required
- Thesis (27 CFU)
- Decision support systems (12 CFU)
Gr1- informatica (18 CFU)
- Advanced laboratory of complex network analysis (6 CFU) - Primo ciclo semestrale
- Information retrieval (6 CFU)
- Technologies for web marketing (6 CFU)
- Visual analytics (6 CFU)
- Programmatic advertising (6 CFU)
- Text analytics (6 CFU)
- Advanced databases (9 CFU)
- Machine learning (9 CFU)
- Social network analysis (6 CFU)
- Distributed data analysis and mining (6 CFU)
- Algorithms and data structures for data science (9 CFU)
- Databases (6 CFU)
- Geospatial analytics (6 CFU)
Career opportunities
- Data scientist
- Data analyst
- Business analyst
- IT Consultants
Enrolment
To enrol, you must hold:
- a university degree recognised as suitable under current legislation
- the curricular requirements specified in the regulations of the degree courses
- adequate personal preparation, assessed according to the procedures defined in the regulations of the degree course.
Pre-registration for the academic year 2026/2027